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Abstract #5637

Quantifying Perfusion Properties with DCE-MRI Using a Dictionary Matching Approach

Satyam Ghodasara1, Sam Frankel1, Yong Chen2, Mark Griswold3, Nicole Seiberlich3, Vikas Gulani3,4,5, and Katherine Wright4

1School of Medicine, Case Western Reserve University, Cleveland, OH, United States, 2Biomedical Engineering, University of North Carolina, Chapel Hill, NC, United States, 3Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States, 4Radiology, Case Western Reserve University, Cleveland, OH, United States, 5Radiology, University Hospitals, Cleveland, OH, United States

To overcome the shortcomings of curve fitting to quantify perfusion properties, a dictionary matching approach like that used in magnetic resonance fingerprinting is proposed. This dictionary matching approach could be used for any DCE application or model, but is demonstrated and validated here for a dual-input single-compartment model of liver DCE-MRI data. The dictionary matching method provides similar results to the curve fitting method while being simpler to implement and dramatically faster.

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